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Microsoft continues to buy very popular mobile applications for the iOS and Android operating systems. Most recently, it announced that it had acquired the London-based development team behind the SwiftKey predictive keyboard for $250 million.

SwiftKey is among the most popular keyboards on iPhones and Android phones, and Microsoft plans to integrate its features into its own Word Flow keyboard for Windows as well. However, it will continue to keep the development for the other two mentioned competing operating systems in operation.

Although Microsoft is also acquiring the application itself as part of the 250 million acquisition, it is most interested in the talent and the entire SwiftKey team, which will join Remond's research initiatives. Microsoft is mainly interested in artificial intelligence work, because in the last update for Android, Swiftkey stopped using traditional algorithms for word prediction and switched to neural networks.

"We believe that together we can achieve success on a much larger scale than we could alone." he declared to the acquisition Harry Shum, Microsoft's head of research.

Positively agree expressed also co-founders of SwiftKey, Jon Reynolds and Ben Medlock: “Microsoft's mission is to enable every person and every business on our planet to do more. Our mission is to improve the interaction between people and technology. We think we are a great match.'

SwiftKey was founded by two then young friends in 2008 because they were convinced that typing on smartphones could be much better. Since then, hundreds of millions of people have installed their app, and according to the co-founders, SwiftKey has saved them roughly 10 trillion individual keystrokes.

The acquisition of SwiftKey just continues the set trend in which Microsoft buys the best mobile apps in order to both expand its teams and the range of services it wants to provide on all platforms. That's why he bought apps last year Sleep as an Droid, Sunrise and thanks to Acompli introduced new Outlook.

Source: SwiftKey, Microsoft
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